Engineering Commons^™

A Framework For Bioacoustic Vocalization Analysis Using Hidden Markov Models, Yao Ren, Michael T. Johnson, Patrick J. Clemins, Michael Darre, Sharon Stuart Glaeser, Tomasz S. Osiejuk, Ebenezer Out-Nyarko

Electrical and Computer Engineering Faculty Research and Publications

Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of …

Analysis And Diagnostics Of Adjacent And Nonadjacent Broken-Rotor-Bar Faults In Squirrel-Cage Induction Machines, Gennadi Y. Sizov, Ahmed Mohamed Sayed Ahmed, Chia-Chou Yeh, Nabeel Demerdash

Electrical and Computer Engineering Faculty Research and Publications

In this paper, faults associated with the rotor of an induction machine are considered. More specifically, effects of adjacent and nonadjacent bar breakages on rotor fault diagnostics in squirrel-cage induction machines are studied. It is shown that some nonadjacent bar breakages may result in the masking of the commonly used fault indices and, hence, may lead to a possible misdiagnosis of the machine. A discussion of the possible scenarios of these breakages as well as some conclusions regarding the types of squirrel-cage induction machines (number of poles, number of squirrel-cage bars, etc.) that may be more prone to these nonadjacent …

Demonstration Of A Bias Tunable Quantum Dots-In-A-Well Focal Plane Array, Jonathan Andrews, Woo-Yong Jang, Jorge E. Pezoa, Yagya D. Sharma, Sang Jun Lee, Sam Kyu Noh, Majeed M. Hayat, Sergio Restaino, Scott W. Teare, Sanjay Krishna

Electrical and Computer Engineering Faculty Research and Publications

Infrared detectors based on quantum wells and quantum dots have attracted a lot of attention in the past few years. Our previous research has reported on the development of the first generation of quantum dots-in-a-well (DWELL) focal plane arrays, which are based on InAs quantum dots embedded in an InGaAs well having GaAs barriers. This focal plane array has successfully generated a two-color imagery in the mid-wave infrared (i.e. 3–5 μm) and the long-wave infrared (i.e. 8–12 μm) at a fixed bias voltage. Recently, the DWELL device has been further modified by embedding InAs quantum dots in InGaAs …

Bit Error Rates For Ultrafast Apd Based Optical Receivers: Exact And Large Deviation Based Asymptotic Approaches, Peng Sun, Majeed M. Hayat, Abhik K. Das

Electrical and Computer Engineering Faculty Research and Publications

Exact analysis as well as asymptotic analysis, based on large-deviation theory (LDT), are developed to compute the bit-error rate (BER) for ultrafast avalanche-photodiode (APD) based optical receivers assuming on-off keying and direct detection. The effects of intersymbol interference (ISI), resulting from the APD's stochastic avalanche buildup time, as well as the APD's dead space are both included in the analysis. ISI becomes a limiting factor as the transmission rate approaches the detector's bandwidth, in which case the bit duration becomes comparable to APD's avalanche buildup time. Further, the effect of dead space becomes significant in high-speed APDs that employ thin …

Optimization Of Inp Apds For High-Speed Lightwave Systems, Daniel S.G. Ong, Jo Shien Ng, Majeed M. Hayat, John P.R. David

Electrical and Computer Engineering Faculty Research and Publications

Calculations based on a rigorous analytical model are carried out to optimize the width of the indium phosphide avalanche region in high-speed direct-detection avalanche photodiode-based optical receivers. The model includes the effects of intersymbol interference (ISI), tunneling current, avalanche noise, and its correlation with the stochastic avalanche duration, as well as dead space. A minimum receiver sensitivity of -28 dBm is predicted at an optimal width of 0.18 mum and an optimal gain of approximately 13, for a 10 Gb/s communication system, assuming a Johnson noise level of 629 noise electrons per bit. The interplay among the factors controlling the …

Efficient Embedded Speech Recognition For Very Large Vocabulary Mandarin Car-Navigation Systems, Yanmin Qian, Jia Liu, Michael T. Johnson

Electrical and Computer Engineering Faculty Research and Publications

Automatic speech recognition (ASR) for a very large vocabulary of isolated words is a difficult task on a resource-limited embedded device. This paper presents a novel fast decoding algorithm for a Mandarin speech recognition system which can simultaneously process hundreds of thousands of items and maintain high recognition accuracy. The proposed algorithm constructs a semi-tree search network based on Mandarin pronunciation rules, to avoid duplicate syllable matching and save redundant memory. Based on a two-stage fixed-width beam-search baseline system, the algorithm employs a variable beam-width pruning strategy and a frame-synchronous word-level pruning strategy to significantly reduce recognition time. This algorithm …

Demonstration Of Bias-Controlled Algorithmic Tuning Of Quantum Dots In A Well (Dwell) Midir Detectors, Woo-Yong Jang, Majeed M. Hayat, J. Scott Tyo, Ram S. Attaluri, Thomas E. Vandervelde, Yagya D. Sharma, Rajeev Shenoi, Andreas Stintz, Elizabeth R. Cantwell, Steven C. Bender, Sang Jun Lee, Sam Kyu Noh, Sanjay Krishna

Electrical and Computer Engineering Faculty Research and Publications

The quantum-confined Stark effect in intersublevel transitions present in quantum-dots-in-a-well (DWELL) detectors gives rise to a midIR spectral response that is dependent upon the detector's operational bias. The spectral responses resulting from different biases exhibit spectral shifts, albeit with significant spectral overlap. A postprocessing algorithm was developed by Sakoglu that exploited this bias-dependent spectral diversity to predict the continuous and arbitrary tunability of the DWELL detector within certain limits. This paper focuses on the experimental demonstration of the DWELL-based spectral tuning algorithm. It is shown experimentally that it is possible to reconstruct the spectral content of a target electronically without …

A Pilot Study Evaluating Use Of A Computer-Assisted Neurorehabilitation Platform For Upper-Extremity Stroke Assessment, Xin Feng, Jack Winters

Electrical and Computer Engineering Faculty Research and Publications

Background

There is a need to develop cost-effective, sensitive stroke assessment instruments. One approach is examining kinematic measures derived from goal-directed tasks, which can potentially be sensitive to the subtle changes in the stroke rehabilitation process. This paper presents the findings from a pilot study that uses a computer-assisted neurorehabilitation platform, interfaced with a conventional force-reflecting joystick, to examine the assessment capability of the system by various types of goal-directed tasks.

Methods

Both stroke subjects with hemiparesis and able-bodied subjects used the force-reflecting joystick to complete a suite of goal-directed tasks under various task settings. Kinematic metrics, developed for specific …

Mathematical Models For Natural Gas Forecasting, Steven Vitullo, Ronald H. Brown, George F. Corliss, Brian M. Marx

Electrical and Computer Engineering Faculty Research and Publications

It is vital for natural gas Local Distribution Companies (LDCs) to forecast their customers' natural gas demand accurately. A significant error on a single very cold day can cost the customers of the LDC millions of dollars. This paper looks at the financial implication of forecasting natural gas, the nature of natural gas forecasting, the factors that impact natural gas consumption, and describes a survey of mathematical techniques and practices used to model natural gas demand. Many of the techniques used in this paper currently are implemented in a software GasDay^TM, which is currently used by 24 LDCs …